Biographical Information

Articles by Alan Pelz-Sharpe

What Problem Is AI Actually Trying to Solve?

Too often, AI is deployed reactively—thrown at symptoms rather than root causes—leading to wasted resources, disillusionment, and even deeper inefficiencies.

Let’s Get Real About the Impact of AI on Jobs

History tells us that industrial revolutions ultimately do create more jobs, but that the transition period is long and highly turbulent. Thus, when we see resistance in the workplace to AI and automation in general, we should acknowledge that the resistance and fear are well-grounded.

Pricing Models on the Horizon

What is inarguable is the fact that enterprise SaaS is incredibly profitable and, by default, incredibly expensive to use over time.

The Long- and Short-Term Impacts of AI Technologies

A much less-known but arguably more critical tech law is Amara's Law, which states that we tend to overestimate the short-term impact of new technology while underestimating its long-term effects.

Agentic AI—So hot right now!

We are in the earliest stages of Agentic AI, and, much like the early days of RPA and GenAI, there's a lot of excitement but also a lot of uncertainty. While the potential benefits are enormous— streamlined operations, lower costs, fewer human errors—there are equally important concerns about job displacement, bias in AI decision making, and a lack of transparency in how these systems operate.

The rise and potential fall of the citizen developer

The citizen developer movement was heralded as a revolution. Like most revolutions, things have sometimes gone differently than planned. The logic is sound, empowering those who know the business best to build the tools and systems needed to do their job. Ah, if only things were that simple …

The end of tech glory days

The tech industry's glory days may be fading a little, but this is not a time for despair. It's an opportunity for renewal. By shifting to a needs-driven approach, the industry can ensure its relevance in a rapidly changing landscape.

The third place of knowledge management

The third place I alluded to goes far beyond mechanistic KM or curated knowledge and takes us into the actual world of tacit knowledge. Here, knowledge comes from and often remains as personal experience, impressions, and intuition; it's undocumented and often hidden and elusive.

Should we go back to paper-based KM?

The sheer volume of largely useless data we have accumulated across the years severely limits the ability of AI to work well, and it comes at a heavy environmental and financial cost.

The trust problem with GenAI

2023 has been the year of ultra-hyping GenAI, and who is paying for this deluge of marketing? Technology vendors that want us to buy it. Again, it's impressive stuff, but when we shift from selling to buying and ultimately using it, many tough questions need to be asked.

When is good enough enough?

Our goal should be to improve the quality of knowledge assets and their accuracy and relevance in use. Much of this will come from human expertise and effort, increasingly combined with the power of AI.

Get your game on: KM skills needed for reliable use of LLMs

There is no questioning that generative AI is here to stay, but its use in mission-critical work has some way to go before it can be trusted and let loose.

The evolution of the KM technology stack

Historically, KM managers have tried to centralize knowledge assets into a single KM platform and curate within it. But outside of a few niche use cases, this has not been feasible for many years. Combining few KM human resources and an increasing data deluge makes it impractical. That is not to say we don't have the tools and resources to manage knowledge assets effectively; rather, we need to recognize corporate realities, be open to innovation, and embrace radical change.

AI technologies upending traditional KM

If we are not careful and proactive about it, the concept and importance of knowledge itself may soon become blurred or lost.

The effect of ChatGPT on KM

At this peak of ChatGPT hype, we have to ask what value it may bring.

Introducing work intelligence systems

Technological advances are significant and can bring huge benefits, but only as long as you understand that they can advise, augment, and support, but not replace, you.

The human capability to under-or overestimate

Yet maybe the most glaring example of underestimating humans we encounter in our work is in the world of AI. It's partly the term "intelligence" in AI that misleads so many, as AI is not intelligent in the same way that humans are intelligent. Though powerful, AI ultimately matches patterns it has learned, and even the smartest of AI systems is limited in how many patterns it can match and make sense of.

To hyperautomate or not to hyperautomate?

The logic behind hyperautomation is clear: Automate everything that can be automated. The practicalities of that are far less clear.

Finding the weakest link

Though traditional and often reluctant to change, the supply chain sector is now reassessing its lack of embrace of technology and, significantly, rethinking long-established processes.

The Law and AI

AI is very good, and light years ahead of where it was just a decade ago, but it is far from "intelligent." Indeed, it is only as good as the data it is provided and needs close human supervision.

Knowledge unchained

Blockchains eliminate the need to trust other people. That's it; that is all there is to it. Trust is deferred to the system itself.

Getting to the future of KM

AI can and does do a good job of assisting and even augmenting knowledge work, but our "to be" state should not take the human element—however flawed—from the work.

From robots to digital workers

As more firms use the term "digital workers" in place of bots, a spotlight is being shone on the role, importance, and increasing controversy surrounding enterprise automation.

The big opportunity for knowledge management

It may well be stating the obvious but we will not be returning to the old ways of working, even though some of us, myself included (as it turns out, I am in the minority), would like to.

Can AI be ethical?

Without inherent bias in the data, AI would not make decisions. Bizarre though it may seem, AI is dependent on bias being present.

How we innovate matters

Just as nobody was fooled by the arguments used to justify offshoring and outsourcing business processes, they should also not be misled by the furious energy behind automation, be it in the form of RPA or even AI.

Reframing the KM discussion

The tech sector is growing fast, but without thorough business analysis, insight, proper planning, and a focus on challenging the better-quicker-cheaper approach and replacing it with a beneficial-adaptable-affordable commitment, there is a world of trouble ahead.

The rise of machine teaching

In contrast to some jobs that can indeed be automated and removed from the human payroll, KM practitioners have the potential to see their skills in much higher demand and volume in the future.

Decentralized knowledge management

Decentralization, though a boon to technology vendors, poses a unique set of challenges and risks for information and knowledge managers to grapple with.

Thinking about KM differently

Moving to a push rather than a pull mentality simply means that we now have the technology to tag, manage, and interpret information automatically and near instantly—automatically pushing the right information to the right person (or application) at the right time.

Thinking beyond the status quo

The technologies exist today to achieve almost any corporate or departmental goal. What is lacking is the nerve to think big and think beyond the status quo—to break barriers, to collaborate, and to share.

The right time for knowledge management

A new generation is coming in—one that sees order in the chaos, spots previously invisible patterns, and not only embraces technology but grew up with it.

The truth and chatbots

A chatbot is a digital language processing service, powered by rules and artificial intelligence that simulates human-like conversation.

Renting KM applications in the CLOUD

The fact is that enterprise needs are complex, and running software on somebody else's infrastructure doesn't take away that complexity. The technology is not the critical failure point these days; it's the application of that technology that falls apart.

Social intranets and the supply chain

Video instant messaging: a misunderstood KM disrupter

Due to ever-falling costs, high-availability data connections, smart mobile devices and the growth of cloud computing, knowledge management and enterprise collaboration in general are undergoing something of a rebirth.

Rethinking enterprise social networks

Outside the organization, too, where social media has the reach and critical mass to make it a viable channel for customer interaction, enterprises are learning that its true value is in helping support the totality of its business activities....

KM in the cloud

"In 2012, every vendor of KM-related technology has a cloud offering and uses the term in as many marketing messages as possible"...

Tracing the ancestry of a product

When organizations buy knowledge and information management technology, they often do so from trusted and preferred suppliers. On the surface, that approach makes a great deal of sense, but a closer look at what is being sold will occasionally make you think twice. Information and knowledge management technology offerings would appear to have evolved in terms of complexity and breadth over the past decade. Yet, some offerings on sale today have long and sometimes infamous heritages, even though their branding and marketing may suggest they are shiny new and "cutting edge." Gaining an understanding of a product's ancestry is essential work to undertake for any technology buyer in today's market.

“Content” technology predictions for 2010

What’s all the hype about?

SharePoint 2010: It's worth looking at SharePoint 2010, what it promises and why so much buzz is being generated.

A component approach to content

In the multichannel, customer-driven world in which we live, the pressure to meet ever-increasing information demands has never been more acute or complex. Yet, the birth of the Extensible Markup Language (XML) file format and the component content management (CCM) systems that leverage XML provide us with the tools to meet those demands. But tools are just that, tools to be used, and without a broader understanding and strategy for their use, they are of little value...

A standard with a chance of success

What is e-mail archiving and management?

You know you have an e-mail management problem, but what kind of problem? Defining the exact nature of your problem can be half the battle to finding a solution.

ECM Market Overview 2008

Without doubt, 2007 was an important transitional year for enterprise content management (ECM). We saw the emergence of the MOI vendors—Microsoft, Oracle and IBM—as serious players in the market, with the dual, and frequently contradictory, goals of bringing ECM to the masses and delivering sweeping content services as core infrastructure.

HOSTED SOLUTIONS: (SaaS): SpringCM

ECM consolidation continues

KM in an unwired enterprise

The eternal document question

Breaking free of the desktop

Knowledge management—Past and future

The electronic records management challenge

Analyst report: FileNet P8

Who knows whom and what

Records management redux: the nudge toward compliance

Turbulent times for DAM

Enterprise content management: Is it anything new?

The next generation of search

The need for portals

E-process technology: Heading in the right direction

Content management tools help support KM solutions

Content management tools help support KM solutions